@article{MAKHILLIJSC201813521453,
    title = {Extraction of Root Words Using Morphological Analyzer for Hindi Text},
    journal = {International Journal of Soft Computing},
    volume = {13},
    number = {5},
    pages = {134-138},
    year = {2018},
    issn = {1816-9503},
    doi = {ijscomp.2018.134.138},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2018.134.138},
    author = {Anjusha and},
    keywords = {Natural language processing,stemmer,suffix stripping,rule based,machine},
    abstract = {Stemming is a process of extracting words from text and turning them into index terms in an
IR system. Stemmers are based upon the written and not the spoken form of the language. Word
stemming is one of the most significant factors that affect the performance of a Natural Language
Processing (NLP) application such as Information Retrieval (IR) system, part of speech tagging, machine
translation system and syntactic parsing, text summarization. A stemmer converts morphologically
identical words to root word without performing analysis of that term. Sometimes, if we remove suffix from the
word then the word may not be a proper Hindi word. So, to overcome this problem, a stemming algorithm is
proposed that uses hybrid approach (combination of Brute force approach, suffix stripping approach and suffix
substitution).}
    }